Pandas Profiling Report

Dataset statistics

Number of variables	15
Number of observations	45984
Missing cells	161745
Missing cells (%)	23.4%
Duplicate rows	0
Duplicate rows (%)	0.0%
Total size in memory	5.3 MiB
Average record size in memory	120.0 B

Variable types

Categorical	6
Numeric	9

Alerts

`country` has a high cardinality: 222 distinct values	High cardinality
`iso_code` has a high cardinality: 222 distinct values	High cardinality
`date` has a high cardinality: 294 distinct values	High cardinality
`vaccines` has a high cardinality: 68 distinct values	High cardinality
`source_name` has a high cardinality: 86 distinct values	High cardinality
`source_website` has a high cardinality: 146 distinct values	High cardinality
`total_vaccinations` is highly correlated with `people_vaccinated` and 3 other fields	High correlation
`people_vaccinated` is highly correlated with `total_vaccinations` and 3 other fields	High correlation
`people_fully_vaccinated` is highly correlated with `total_vaccinations` and 5 other fields	High correlation
`daily_vaccinations_raw` is highly correlated with `total_vaccinations` and 3 other fields	High correlation
`daily_vaccinations` is highly correlated with `total_vaccinations` and 3 other fields	High correlation
`total_vaccinations_per_hundred` is highly correlated with `people_fully_vaccinated` and 3 other fields	High correlation
`people_vaccinated_per_hundred` is highly correlated with `total_vaccinations_per_hundred` and 2 other fields	High correlation
`people_fully_vaccinated_per_hundred` is highly correlated with `people_fully_vaccinated` and 3 other fields	High correlation
`daily_vaccinations_per_million` is highly correlated with `total_vaccinations_per_hundred` and 2 other fields	High correlation
`total_vaccinations` is highly correlated with `people_vaccinated` and 3 other fields	High correlation
`people_vaccinated` is highly correlated with `total_vaccinations` and 3 other fields	High correlation
`people_fully_vaccinated` is highly correlated with `total_vaccinations` and 3 other fields	High correlation
`daily_vaccinations_raw` is highly correlated with `total_vaccinations` and 3 other fields	High correlation
`daily_vaccinations` is highly correlated with `total_vaccinations` and 3 other fields	High correlation
`total_vaccinations_per_hundred` is highly correlated with `people_vaccinated_per_hundred` and 1 other fields	High correlation
`people_vaccinated_per_hundred` is highly correlated with `total_vaccinations_per_hundred` and 1 other fields	High correlation
`people_fully_vaccinated_per_hundred` is highly correlated with `total_vaccinations_per_hundred` and 1 other fields	High correlation
`total_vaccinations` is highly correlated with `people_vaccinated` and 3 other fields	High correlation
`people_vaccinated` is highly correlated with `total_vaccinations` and 3 other fields	High correlation
`people_fully_vaccinated` is highly correlated with `total_vaccinations` and 3 other fields	High correlation
`daily_vaccinations_raw` is highly correlated with `total_vaccinations` and 3 other fields	High correlation
`daily_vaccinations` is highly correlated with `total_vaccinations` and 3 other fields	High correlation
`total_vaccinations_per_hundred` is highly correlated with `people_vaccinated_per_hundred` and 2 other fields	High correlation
`people_vaccinated_per_hundred` is highly correlated with `total_vaccinations_per_hundred` and 2 other fields	High correlation
`people_fully_vaccinated_per_hundred` is highly correlated with `total_vaccinations_per_hundred` and 1 other fields	High correlation
`daily_vaccinations_per_million` is highly correlated with `total_vaccinations_per_hundred` and 1 other fields	High correlation
`vaccines` is highly correlated with `source_name`	High correlation
`source_name` is highly correlated with `vaccines`	High correlation
`total_vaccinations` is highly correlated with `people_vaccinated` and 5 other fields	High correlation
`people_vaccinated` is highly correlated with `total_vaccinations` and 5 other fields	High correlation
`people_fully_vaccinated` is highly correlated with `total_vaccinations` and 5 other fields	High correlation
`daily_vaccinations_raw` is highly correlated with `total_vaccinations` and 5 other fields	High correlation
`daily_vaccinations` is highly correlated with `total_vaccinations` and 5 other fields	High correlation
`total_vaccinations_per_hundred` is highly correlated with `people_vaccinated_per_hundred` and 3 other fields	High correlation
`people_vaccinated_per_hundred` is highly correlated with `total_vaccinations_per_hundred` and 3 other fields	High correlation
`people_fully_vaccinated_per_hundred` is highly correlated with `total_vaccinations_per_hundred` and 3 other fields	High correlation
`vaccines` is highly correlated with `total_vaccinations` and 8 other fields	High correlation
`source_name` is highly correlated with `total_vaccinations` and 8 other fields	High correlation
`total_vaccinations` has 20900 (45.5%) missing values	Missing
`people_vaccinated` has 22038 (47.9%) missing values	Missing
`people_fully_vaccinated` has 24935 (54.2%) missing values	Missing
`daily_vaccinations_raw` has 25384 (55.2%) missing values	Missing
`total_vaccinations_per_hundred` has 20900 (45.5%) missing values	Missing
`people_vaccinated_per_hundred` has 22038 (47.9%) missing values	Missing
`people_fully_vaccinated_per_hundred` has 24936 (54.2%) missing values	Missing
`people_fully_vaccinated` is highly skewed (γ1 = 21.0654483)	Skewed
`people_fully_vaccinated_per_hundred` has 475 (1.0%) zeros	Zeros

Reproduction

Analysis started	2021-10-30 23:03:55.362949
Analysis finished	2021-10-30 23:04:17.083665
Duration	21.72 seconds
Software version	pandas-profiling v3.1.0
Download configuration	config.json

country
Categorical

HIGH CARDINALITY

Distinct	222
Distinct (%)	0.5%
Missing	0
Missing (%)	0.0%
Memory size	359.4 KiB

Denmark	293
Norway	292
Latvia	291
Scotland	286
England	286
Other values (217)	44536

Length

Max length	32
Median length	7
Mean length	8.732559151
Min length	4

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	1 ?
Unique (%)	< 0.1%

Sample

1st row	Afghanistan
2nd row	Afghanistan
3rd row	Afghanistan
4th row	Afghanistan
5th row	Afghanistan

Common Values

Value	Count	Frequency (%)
Denmark	293	0.6%
Norway	292	0.6%
Latvia	291	0.6%
Scotland	286	0.6%
England	286	0.6%
Wales	281	0.6%
Canada	281	0.6%
United Kingdom	281	0.6%
Northern Ireland	281	0.6%
China	280	0.6%
Other values (212)	43132	93.8%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
and	1790	3.0%
islands	1199	2.0%
united	815	1.4%
saint	697	1.2%
new	608	1.0%
south	587	1.0%
ireland	544	0.9%
guinea	521	0.9%
northern	495	0.8%
republic	494	0.8%
Other values (249)	51901	87.0%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

iso_code
Categorical

HIGH CARDINALITY

Distinct	222
Distinct (%)	0.5%
Missing	0
Missing (%)	0.0%
Memory size	359.4 KiB

DNK	293
NOR	292
LVA	291
OWID_ENG	286
OWID_SCT	286
Other values (217)	44536

Length

Max length	8
Median length	3
Mean length	3.165818546
Min length	3

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	1 ?
Unique (%)	< 0.1%

Sample

1st row	AFG
2nd row	AFG
3rd row	AFG
4th row	AFG
5th row	AFG

Common Values

Value	Count	Frequency (%)
DNK	293	0.6%
NOR	292	0.6%
LVA	291	0.6%
OWID_ENG	286	0.6%
OWID_SCT	286	0.6%
GBR	281	0.6%
CAN	281	0.6%
OWID_WLS	281	0.6%
OWID_NIR	281	0.6%
RUS	280	0.6%
Other values (212)	43132	93.8%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
dnk	293	0.6%
nor	292	0.6%
lva	291	0.6%
owid_eng	286	0.6%
owid_sct	286	0.6%
gbr	281	0.6%
can	281	0.6%
owid_wls	281	0.6%
owid_nir	281	0.6%
rus	280	0.6%
Other values (212)	43132	93.8%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

date
Categorical

HIGH CARDINALITY

Distinct	294
Distinct (%)	0.6%
Missing	0
Missing (%)	0.0%
Memory size	359.4 KiB

02-08-2021	217
20-07-2021	217
10-08-2021	217
18-07-2021	217
27-07-2021	217
Other values (289)	44899

Length

Max length	10
Median length	10
Mean length	10
Min length	10

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	1 ?
Unique (%)	< 0.1%

Sample

1st row	22-02-2021
2nd row	23-02-2021
3rd row	24-02-2021
4th row	25-02-2021
5th row	26-02-2021

Common Values

Value	Count	Frequency (%)
02-08-2021	217	0.5%
20-07-2021	217	0.5%
10-08-2021	217	0.5%
18-07-2021	217	0.5%
27-07-2021	217	0.5%
08-08-2021	217	0.5%
29-06-2021	217	0.5%
29-07-2021	217	0.5%
28-06-2021	217	0.5%
21-06-2021	217	0.5%
Other values (284)	43814	95.3%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
02-08-2021	217	0.5%
19-07-2021	217	0.5%
20-07-2021	217	0.5%
15-08-2021	217	0.5%
26-07-2021	217	0.5%
24-06-2021	217	0.5%
27-06-2021	217	0.5%
14-08-2021	217	0.5%
12-08-2021	217	0.5%
22-06-2021	217	0.5%
Other values (284)	43814	95.3%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

total_vaccinations
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct	24534
Distinct (%)	97.8%
Missing	20900
Missing (%)	45.5%
Infinite	0
Infinite (%)	0.0%
Mean	20487937.01

Minimum	0
Maximum	2180986000
Zeros	139
Zeros (%)	0.3%
Negative	0
Negative (%)	0.0%
Memory size	359.4 KiB

Quantile statistics

Minimum	0
5-th percentile	13614.7
Q1	207767.75
median	1459863
Q3	7737194
95-th percentile	68620795.95
Maximum	2180986000
Range	2180986000
Interquartile range (IQR)	7529426.25

Descriptive statistics

Standard deviation	117360316.8
Coefficient of variation (CV)	5.728264236
Kurtosis	196.3500563
Mean	20487937.01
Median Absolute Deviation (MAD)	1417767
Skewness	13.05852627
Sum	5.139194119 × 10¹¹
Variance	1.377344397 × 10¹⁶
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
0	139	0.3%
39207	17	< 0.1%
43139	11	< 0.1%
8655	8	< 0.1%
10708	7	< 0.1%
6	6	< 0.1%
38572	6	< 0.1%
2	5	< 0.1%
841	5	< 0.1%
846	5	< 0.1%
Other values (24524)	24875	54.1%
(Missing)	20900	45.5%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	139	0.3%
1	3	< 0.1%
2	5	< 0.1%
3	2	< 0.1%
4	2	< 0.1%
5	2	< 0.1%
6	6	< 0.1%
7	2	< 0.1%
9	1	< 0.1%
11	1	< 0.1%

Value	Count	Frequency (%)
2180986000	1	< 0.1%
2177638000	1	< 0.1%
2174043000	1	< 0.1%
2170017000	1	< 0.1%
2165679000	1	< 0.1%
2161428000	1	< 0.1%
2156938000	1	< 0.1%
2152520000	1	< 0.1%
2148120000	1	< 0.1%
2142580000	1	< 0.1%

people_vaccinated
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct	23212
Distinct (%)	96.9%
Missing	22038
Missing (%)	47.9%
Infinite	0
Infinite (%)	0.0%
Mean	8757992.75

Minimum	0
Maximum	1100842000
Zeros	129
Zeros (%)	0.3%
Negative	0
Negative (%)	0.0%
Memory size	359.4 KiB

Quantile statistics

Minimum	0
5-th percentile	11559
Q1	166852.5
median	998103.5
Q3	4679777.5
95-th percentile	38529067.5
Maximum	1100842000
Range	1100842000
Interquartile range (IQR)	4512925

Descriptive statistics

Standard deviation	34301725.71
Coefficient of variation (CV)	3.91661956
Kurtosis	223.2831084
Mean	8757992.75
Median Absolute Deviation (MAD)	967123.5
Skewness	12.08574061
Sum	2.097188944 × 10¹¹
Variance	1.176608387 × 10¹⁵
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
0	129	0.3%
5823245	28	0.1%
2113080	13	< 0.1%
24773	10	< 0.1%
486242	10	< 0.1%
928107	8	< 0.1%
8655	8	< 0.1%
10708	7	< 0.1%
142125	7	< 0.1%
2611807	6	< 0.1%
Other values (23202)	23720	51.6%
(Missing)	22038	47.9%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	129	0.3%
1	3	< 0.1%
2	5	< 0.1%
3	2	< 0.1%
4	2	< 0.1%
5	2	< 0.1%
6	6	< 0.1%
7	2	< 0.1%
9	1	< 0.1%
11	1	< 0.1%

Value	Count	Frequency (%)
1100842000	1	< 0.1%
1095000000	1	< 0.1%
1072500000	1	< 0.1%
622000000	1	< 0.1%
606563237	1	< 0.1%
602206789	1	< 0.1%
597205296	1	< 0.1%
586105233	1	< 0.1%
582842108	1	< 0.1%
576856263	1	< 0.1%

people_fully_vaccinated
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING
SKEWED

Distinct	20122
Distinct (%)	95.6%
Missing	24935
Missing (%)	54.2%
Infinite	0
Infinite (%)	0.0%
Mean	5583140.034

Minimum	1
Maximum	1022207000
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	359.4 KiB

Quantile statistics

Minimum	1
5-th percentile	3451.2
Q1	80363
median	635314
Q3	3270303
95-th percentile	27643648.2
Maximum	1022207000
Range	1022206999
Interquartile range (IQR)	3189940

Descriptive statistics

Standard deviation	22116692.76
Coefficient of variation (CV)	3.961335848
Kurtosis	795.5951026
Mean	5583140.034
Median Absolute Deviation (MAD)	620003
Skewness	21.0654483
Sum	1.175195146 × 10¹¹
Variance	4.891480985 × 10¹⁴
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
1	69	0.2%
2	33	0.1%
5	31	0.1%
1179	27	0.1%
6	20	< 0.1%
19019	20	< 0.1%
3	18	< 0.1%
7	17	< 0.1%
8	16	< 0.1%
341	14	< 0.1%
Other values (20112)	20784	45.2%
(Missing)	24935	54.2%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
1	69	0.2%
2	33	0.1%
3	18	< 0.1%
4	10	< 0.1%
5	31	0.1%
6	20	< 0.1%
7	17	< 0.1%
8	16	< 0.1%
9	8	< 0.1%
10	8	< 0.1%

Value	Count	Frequency (%)
1022207000	1	< 0.1%
1011584000	1	< 0.1%
969720000	1	< 0.1%
889439000	1	< 0.1%
777046000	1	< 0.1%
205669279	1	< 0.1%
202571907	1	< 0.1%
198809823	1	< 0.1%
191282617	1	< 0.1%
188499533	1	< 0.1%

daily_vaccinations_raw
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct	17407
Distinct (%)	84.5%
Missing	25384
Missing (%)	55.2%
Infinite	0
Infinite (%)	0.0%
Mean	259785.02

Minimum	0
Maximum	24741000
Zeros	240
Zeros (%)	0.5%
Negative	0
Negative (%)	0.0%
Memory size	359.4 KiB

Quantile statistics

Minimum	0
5-th percentile	297
Q1	4898
median	24106.5
Q3	111688.75
95-th percentile	734813.45
Maximum	24741000
Range	24741000
Interquartile range (IQR)	106790.75

Descriptive statistics

Standard deviation	1317280.917
Coefficient of variation (CV)	5.070657717
Kurtosis	142.5510671
Mean	259785.02
Median Absolute Deviation (MAD)	23000.5
Skewness	11.10058644
Sum	5351571413
Variance	1.735229013 × 10¹²
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
0	240	0.5%
1	37	0.1%
3	14	< 0.1%
4	13	< 0.1%
5	11	< 0.1%
2	10	< 0.1%
30	9	< 0.1%
7	9	< 0.1%
1025	8	< 0.1%
8	8	< 0.1%
Other values (17397)	20241	44.0%
(Missing)	25384	55.2%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	240	0.5%
1	37	0.1%
2	10	< 0.1%
3	14	< 0.1%
4	13	< 0.1%
5	11	< 0.1%
6	4	< 0.1%
7	9	< 0.1%
8	8	< 0.1%
9	5	< 0.1%

Value	Count	Frequency (%)
24741000	1	< 0.1%
24119000	1	< 0.1%
23605000	1	< 0.1%
23162000	1	< 0.1%
22918000	1	< 0.1%
22296000	1	< 0.1%
22039000	1	< 0.1%
21502000	1	< 0.1%
21425000	1	< 0.1%
21240000	1	< 0.1%

daily_vaccinations
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	24529
Distinct (%)	53.7%
Missing	307
Missing (%)	0.7%
Infinite	0
Infinite (%)	0.0%
Mean	130853.5448

Minimum	0
Maximum	22424286
Zeros	204
Zeros (%)	0.4%
Negative	0
Negative (%)	0.0%
Memory size	359.4 KiB

Quantile statistics

Minimum	0
5-th percentile	75
Q1	871
median	6774
Q3	41695
95-th percentile	419247
Maximum	22424286
Range	22424286
Interquartile range (IQR)	40824

Descriptive statistics

Standard deviation	875853.8116
Coefficient of variation (CV)	6.693390024
Kurtosis	304.4140463
Mean	130853.5448
Median Absolute Deviation (MAD)	6598
Skewness	16.13645739
Sum	5976997368
Variance	7.671198993 × 10¹¹
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
0	204	0.4%
22369	176	0.4%
196	158	0.3%
1	111	0.2%
312	88	0.2%
202	80	0.2%
57	80	0.2%
425	78	0.2%
4	77	0.2%
2	74	0.2%
Other values (24519)	44551	96.9%
(Missing)	307	0.7%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	204	0.4%
1	111	0.2%
2	74	0.2%
3	29	0.1%
4	77	0.2%
5	27	0.1%
6	33	0.1%
7	30	0.1%
8	18	< 0.1%
9	17	< 0.1%

Value	Count	Frequency (%)
22424286	1	< 0.1%
22366286	1	< 0.1%
22105857	1	< 0.1%
21998714	1	< 0.1%
21993000	1	< 0.1%
21935429	1	< 0.1%
21536000	1	< 0.1%
21253286	1	< 0.1%
21124714	1	< 0.1%
20801429	1	< 0.1%

total_vaccinations_per_hundred
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct	10351
Distinct (%)	41.3%
Missing	20900
Missing (%)	45.5%
Infinite	0
Infinite (%)	0.0%
Mean	43.74065859

Minimum	0
Maximum	235.39
Zeros	245
Zeros (%)	0.5%
Negative	0
Negative (%)	0.0%
Memory size	359.4 KiB

Quantile statistics

Minimum	0
5-th percentile	0.29
Q1	5.27
median	26.44
Q3	73.4425
95-th percentile	132.6285
Maximum	235.39
Range	235.39
Interquartile range (IQR)	68.1725

Descriptive statistics

Standard deviation	45.0444271
Coefficient of variation (CV)	1.029806787
Kurtosis	0.116460321
Mean	43.74065859
Median Absolute Deviation (MAD)	24.475
Skewness	1.002541199
Sum	1097190.68
Variance	2029.000413
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
0	245	0.5%
0.01	95	0.2%
0.02	70	0.2%
0.06	57	0.1%
0.07	55	0.1%
0.04	54	0.1%
0.05	53	0.1%
0.03	50	0.1%
0.1	37	0.1%
0.12	37	0.1%
Other values (10341)	24331	52.9%
(Missing)	20900	45.5%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	245	0.5%
0.01	95	0.2%
0.02	70	0.2%
0.03	50	0.1%
0.04	54	0.1%
0.05	53	0.1%
0.06	57	0.1%
0.07	55	0.1%
0.08	30	0.1%
0.09	34	0.1%

Value	Count	Frequency (%)
235.39	1	< 0.1%
235.28	1	< 0.1%
235.18	1	< 0.1%
235.05	1	< 0.1%
234.83	1	< 0.1%
234.7	1	< 0.1%
234.56	1	< 0.1%
234.53	1	< 0.1%
234.37	1	< 0.1%
234.15	1	< 0.1%

people_vaccinated_per_hundred
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct	7071
Distinct (%)	29.5%
Missing	22038
Missing (%)	47.9%
Infinite	0
Infinite (%)	0.0%
Mean	26.56949804

Minimum	0
Maximum	118.27
Zeros	228
Zeros (%)	0.5%
Negative	0
Negative (%)	0.0%
Memory size	359.4 KiB

Quantile statistics

Minimum	0
5-th percentile	0.28
Q1	4.1125
median	18.6
Q3	46.3
95-th percentile	71.1
Maximum	118.27
Range	118.27
Interquartile range (IQR)	42.1875

Descriptive statistics

Standard deviation	24.458658
Coefficient of variation (CV)	0.9205540114
Kurtosis	-0.6370711252
Mean	26.56949804
Median Absolute Deviation (MAD)	16.65
Skewness	0.6922236367
Sum	636233.2
Variance	598.2259511
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
0	228	0.5%
0.01	93	0.2%
0.02	69	0.2%
0.07	64	0.1%
3.5	62	0.1%
0.04	53	0.1%
0.05	52	0.1%
0.06	51	0.1%
0.03	48	0.1%
0.24	39	0.1%
Other values (7061)	23187	50.4%
(Missing)	22038	47.9%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	228	0.5%
0.01	93	0.2%
0.02	69	0.2%
0.03	48	0.1%
0.04	53	0.1%
0.05	52	0.1%
0.06	51	0.1%
0.07	64	0.1%
0.08	22	< 0.1%
0.09	36	0.1%

Value	Count	Frequency (%)
118.27	1	< 0.1%
118.24	1	< 0.1%
118.2	1	< 0.1%
118.16	1	< 0.1%
118.09	1	< 0.1%
118.05	1	< 0.1%
118	2	< 0.1%
117.92	1	< 0.1%
117.71	1	< 0.1%
117.62	1	< 0.1%

people_fully_vaccinated_per_hundred
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING
ZEROS

Distinct	6043
Distinct (%)	28.7%
Missing	24936
Missing (%)	54.2%
Infinite	0
Infinite (%)	0.0%
Mean	19.68974249

Minimum	0
Maximum	117.12
Zeros	475
Zeros (%)	1.0%
Negative	0
Negative (%)	0.0%
Memory size	359.4 KiB

Quantile statistics

Minimum	0
5-th percentile	0.07
Q1	2.3
median	10.645
Q3	32.2525
95-th percentile	62.9065
Maximum	117.12
Range	117.12
Interquartile range (IQR)	29.9525

Descriptive statistics

Standard deviation	21.46713526
Coefficient of variation (CV)	1.090269985
Kurtosis	0.5469886012
Mean	19.68974249
Median Absolute Deviation (MAD)	9.915
Skewness	1.14982895
Sum	414429.7
Variance	460.8378962
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
0	475	1.0%
0.01	178	0.4%
0.02	99	0.2%
0.08	87	0.2%
0.04	84	0.2%
0.03	83	0.2%
0.07	64	0.1%
0.05	64	0.1%
0.06	58	0.1%
0.29	57	0.1%
Other values (6033)	19799	43.1%
(Missing)	24936	54.2%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	475	1.0%
0.01	178	0.4%
0.02	99	0.2%
0.03	83	0.2%
0.04	84	0.2%
0.05	64	0.1%
0.06	58	0.1%
0.07	64	0.1%
0.08	87	0.2%
0.09	41	0.1%

Value	Count	Frequency (%)
117.12	1	< 0.1%
117.04	1	< 0.1%
116.97	1	< 0.1%
116.89	1	< 0.1%
116.74	1	< 0.1%
116.65	1	< 0.1%
116.56	1	< 0.1%
116.52	1	< 0.1%
116.45	1	< 0.1%
116.44	1	< 0.1%

daily_vaccinations_per_million
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION

Distinct	10997
Distinct (%)	24.1%
Missing	307
Missing (%)	0.7%
Infinite	0
Infinite (%)	0.0%
Mean	3547.60352

Minimum	0
Maximum	117497
Zeros	255
Zeros (%)	0.6%
Negative	0
Negative (%)	0.0%
Memory size	359.4 KiB

Quantile statistics

Minimum	0
5-th percentile	43
Q1	505
median	2191
Q3	5307
95-th percentile	10735.4
Maximum	117497
Range	117497
Interquartile range (IQR)	4802

Descriptive statistics

Standard deviation	4429.261509
Coefficient of variation (CV)	1.248522132
Kurtosis	66.83767559
Mean	3547.60352
Median Absolute Deviation (MAD)	1925
Skewness	4.861220497
Sum	162043886
Variance	19618357.52
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
0	255	0.6%
501	184	0.4%
7412	148	0.3%
176	145	0.3%
43	141	0.3%
4	102	0.2%
28	95	0.2%
3	84	0.2%
15	84	0.2%
7954	78	0.2%
Other values (10987)	44361	96.5%
(Missing)	307	0.7%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	255	0.6%
1	65	0.1%
2	67	0.1%
3	84	0.2%
4	102	0.2%
5	65	0.1%
6	25	0.1%
7	67	0.1%
8	69	0.2%
9	58	0.1%

Value	Count	Frequency (%)
117497	1	< 0.1%
117410	1	< 0.1%
110205	1	< 0.1%
109282	1	< 0.1%
101235	1	< 0.1%
92926	1	< 0.1%
83086	1	< 0.1%
78604	1	< 0.1%
73854	1	< 0.1%
72868	1	< 0.1%

vaccines
Categorical

HIGH CARDINALITY
HIGH CORRELATION
HIGH CORRELATION

Distinct	68
Distinct (%)	0.1%
Missing	0
Missing (%)	0.0%
Memory size	359.4 KiB

Johnson&Johnson, Moderna, Oxford/AstraZeneca, Pfizer/BioNTech	5952
Oxford/AstraZeneca	5565
Moderna, Oxford/AstraZeneca, Pfizer/BioNTech	3742
Oxford/AstraZeneca, Sinopharm/Beijing	3038
Oxford/AstraZeneca, Pfizer/BioNTech	3015
Other values (63)	24672

Length

Max length	101
Median length	44
Mean length	44.43786969
Min length	7

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	1 ?
Unique (%)	< 0.1%

Sample

1st row	Johnson&Johnson, Oxford/AstraZeneca, Pfizer/BioNTech, Sinopharm/Beijing
2nd row	Johnson&Johnson, Oxford/AstraZeneca, Pfizer/BioNTech, Sinopharm/Beijing
3rd row	Johnson&Johnson, Oxford/AstraZeneca, Pfizer/BioNTech, Sinopharm/Beijing
4th row	Johnson&Johnson, Oxford/AstraZeneca, Pfizer/BioNTech, Sinopharm/Beijing
5th row	Johnson&Johnson, Oxford/AstraZeneca, Pfizer/BioNTech, Sinopharm/Beijing

Common Values

Value	Count	Frequency (%)
Johnson&Johnson, Moderna, Oxford/AstraZeneca, Pfizer/BioNTech	5952	12.9%
Oxford/AstraZeneca	5565	12.1%
Moderna, Oxford/AstraZeneca, Pfizer/BioNTech	3742	8.1%
Oxford/AstraZeneca, Sinopharm/Beijing	3038	6.6%
Oxford/AstraZeneca, Pfizer/BioNTech	3015	6.6%
Moderna, Pfizer/BioNTech	1939	4.2%
Pfizer/BioNTech	1724	3.7%
Oxford/AstraZeneca, Pfizer/BioNTech, Sinopharm/Beijing, Sputnik V	1618	3.5%
Oxford/AstraZeneca, Pfizer/BioNTech, Sinopharm/Beijing	887	1.9%
Oxford/AstraZeneca, Sputnik V	822	1.8%
Other values (58)	17682	38.5%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
oxford/astrazeneca	37538	25.6%
pfizer/biontech	29892	20.4%
moderna	17354	11.8%
sinopharm/beijing	14024	9.6%
johnson&johnson	11396	7.8%
sputnik	10811	7.4%
v	10811	7.4%
sinovac	8661	5.9%
cansino	1768	1.2%
covaxin	1410	1.0%
Other values (10)	2818	1.9%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

source_name
Categorical

HIGH CARDINALITY
HIGH CORRELATION
HIGH CORRELATION

Distinct	86
Distinct (%)	0.2%
Missing	0
Missing (%)	0.0%
Memory size	359.4 KiB

Ministry of Health	10669
World Health Organization	9926
SPC Public Health Division	1917
Pan American Health Organization	1582
Government of the United Kingdom	1415
Other values (81)	20475

Length

Max length	70
Median length	25
Mean length	26.8049104
Min length	9

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	World Health Organization
2nd row	World Health Organization
3rd row	World Health Organization
4th row	World Health Organization
5th row	World Health Organization

Common Values

Value	Count	Frequency (%)
Ministry of Health	10669	23.2%
World Health Organization	9926	21.6%
SPC Public Health Division	1917	4.2%
Pan American Health Organization	1582	3.4%
Government of the United Kingdom	1415	3.1%
Africa Centres for Disease Control and Prevention	1271	2.8%
Federal Office of Public Health	544	1.2%
Ministry of Public Health	488	1.1%
Statens Serum Institute	293	0.6%
Norwegian Institute of Public Health	292	0.6%
Other values (76)	17587	38.2%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
health	30246	17.6%
of	23316	13.5%
ministry	12013	7.0%
organization	11508	6.7%
world	9926	5.8%
government	8997	5.2%
public	4886	2.8%
for	3177	1.8%
and	3101	1.8%
via	2916	1.7%
Other values (146)	62223	36.1%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

source_website
Categorical

HIGH CARDINALITY

Distinct	146
Distinct (%)	0.3%
Missing	0
Missing (%)	0.0%
Memory size	359.4 KiB

https://covid19.who.int/	7530
https://stats.pacificdata.org/vis?tm=covid&pg=0&df[ds]=SPC2&df[id]=DF_COVID_VACCINATION&df[ag]=SPC&df[vs]=1.0	2020
https://africacdc.org/covid-19-vaccination/	1719
https://ais.paho.org/imm/IM_DosisAdmin-Vacunacion.asp	1519
https://coronavirus.data.gov.uk/details/vaccinations	1415
Other values (141)	31781

Length

Max length	170
Median length	51
Mean length	56.42473469
Min length	16

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	https://app.powerbi.com/view?r=eyJrIjoiYTkyM2VmMDUtNDJjOC00YjU2LWI3Y2MtNTRhMWY4YzU0YTRlIiwidCI6ImY2MTBjMGI3LWJkMjQtNGIzOS04MTBiLTNkYzI4MGFmYjU5MCIsImMiOjh9
2nd row	https://app.powerbi.com/view?r=eyJrIjoiYTkyM2VmMDUtNDJjOC00YjU2LWI3Y2MtNTRhMWY4YzU0YTRlIiwidCI6ImY2MTBjMGI3LWJkMjQtNGIzOS04MTBiLTNkYzI4MGFmYjU5MCIsImMiOjh9
3rd row	https://app.powerbi.com/view?r=eyJrIjoiYTkyM2VmMDUtNDJjOC00YjU2LWI3Y2MtNTRhMWY4YzU0YTRlIiwidCI6ImY2MTBjMGI3LWJkMjQtNGIzOS04MTBiLTNkYzI4MGFmYjU5MCIsImMiOjh9
4th row	https://app.powerbi.com/view?r=eyJrIjoiYTkyM2VmMDUtNDJjOC00YjU2LWI3Y2MtNTRhMWY4YzU0YTRlIiwidCI6ImY2MTBjMGI3LWJkMjQtNGIzOS04MTBiLTNkYzI4MGFmYjU5MCIsImMiOjh9
5th row	https://app.powerbi.com/view?r=eyJrIjoiYTkyM2VmMDUtNDJjOC00YjU2LWI3Y2MtNTRhMWY4YzU0YTRlIiwidCI6ImY2MTBjMGI3LWJkMjQtNGIzOS04MTBiLTNkYzI4MGFmYjU5MCIsImMiOjh9

Common Values

Value	Count	Frequency (%)
https://covid19.who.int/	7530	16.4%
https://stats.pacificdata.org/vis?tm=covid&pg=0&df[ds]=SPC2&df[id]=DF_COVID_VACCINATION&df[ag]=SPC&df[vs]=1.0	2020	4.4%
https://africacdc.org/covid-19-vaccination/	1719	3.7%
https://ais.paho.org/imm/IM_DosisAdmin-Vacunacion.asp	1519	3.3%
https://coronavirus.data.gov.uk/details/vaccinations	1415	3.1%
https://who.maps.arcgis.com/apps/dashboards/ead3c6475654481ca51c248d52ab9c61	476	1.0%
https://www.who.int/southeastasia/health-topics/immunization/covid-19-vaccination	398	0.9%
https://covid19.ssi.dk/overvagningsdata/download-fil-med-vaccinationsdata	293	0.6%
https://www.fhi.no/sv/vaksine/koronavaksinasjonsprogrammet/koronavaksinasjonsstatistikk/	292	0.6%
https://data.gov.lv/dati/eng/dataset/covid19-vakcinacijas	291	0.6%
Other values (136)	30031	65.3%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
https://covid19.who.int	7573	16.5%
https://stats.pacificdata.org/vis?tm=covid&pg=0&df[ds]=spc2&df[id]=df_covid_vaccination&df[ag]=spc&df[vs]=1.0	2020	4.4%
https://africacdc.org/covid-19-vaccination	1719	3.7%
https://ais.paho.org/imm/im_dosisadmin-vacunacion.asp	1519	3.3%
https://coronavirus.data.gov.uk/details/vaccinations	1415	3.1%
https://who.maps.arcgis.com/apps/dashboards/ead3c6475654481ca51c248d52ab9c61	476	1.0%
https://www.who.int/southeastasia/health-topics/immunization/covid-19-vaccination	398	0.9%
https://covid19.ssi.dk/overvagningsdata/download-fil-med-vaccinationsdata	293	0.6%
https://www.fhi.no/sv/vaksine/koronavaksinasjonsprogrammet/koronavaksinasjonsstatistikk	292	0.6%
https://data.gov.lv/dati/eng/dataset/covid19-vakcinacijas	291	0.6%
Other values (135)	29988	65.2%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

Spearman's ρ

The Spearman's rank correlation coefficient (ρ) is a measure of monotonic correlation between two variables, and is therefore better in catching nonlinear monotonic correlations than Pearson's r. It's value lies between -1 and +1, -1 indicating total negative monotonic correlation, 0 indicating no monotonic correlation and 1 indicating total positive monotonic correlation.

To calculate ρ for two variables X and Y, one divides the covariance of the rank variables of X and Y by the product of their standard deviations.

Pearson's r

The Pearson's correlation coefficient (r) is a measure of linear correlation between two variables. It's value lies between -1 and +1, -1 indicating total negative linear correlation, 0 indicating no linear correlation and 1 indicating total positive linear correlation. Furthermore, r is invariant under separate changes in location and scale of the two variables, implying that for a linear function the angle to the x-axis does not affect r.

To calculate r for two variables X and Y, one divides the covariance of X and Y by the product of their standard deviations.

Kendall's τ

Similarly to Spearman's rank correlation coefficient, the Kendall rank correlation coefficient (τ) measures ordinal association between two variables. It's value lies between -1 and +1, -1 indicating total negative correlation, 0 indicating no correlation and 1 indicating total positive correlation.

To calculate τ for two variables X and Y, one determines the number of concordant and discordant pairs of observations. τ is given by the number of concordant pairs minus the discordant pairs divided by the total number of pairs.

Cramér's V (φc)

Cramér's V is an association measure for nominal random variables. The coefficient ranges from 0 to 1, with 0 indicating independence and 1 indicating perfect association. The empirical estimators used for Cramér's V have been proved to be biased, even for large samples. We use a bias-corrected measure that has been proposed by Bergsma in 2013 that can be found here.

Phik (φk)

Phik (φk) is a new and practical correlation coefficient that works consistently between categorical, ordinal and interval variables, captures non-linear dependency and reverts to the Pearson correlation coefficient in case of a bivariate normal input distribution. There is extensive documentation available here.

A simple visualization of nullity by column.

Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

The dendrogram allows you to more fully correlate variable completion, revealing trends deeper than the pairwise ones visible in the correlation heatmap.

First rows

	country	iso_code	date	total_vaccinations	people_vaccinated	people_fully_vaccinated	daily_vaccinations_raw	daily_vaccinations	total_vaccinations_per_hundred	people_vaccinated_per_hundred	people_fully_vaccinated_per_hundred	daily_vaccinations_per_million	vaccines	source_name	source_website
0	Afghanistan	AFG	22-02-2021	0.0	0.0	NaN	NaN	NaN	0.00	0.00	NaN	NaN	Johnson&Johnson, Oxford/AstraZeneca, Pfizer/BioNTech, Sinopharm/Beijing	World Health Organization	https://app.powerbi.com/view?r=eyJrIjoiYTkyM2VmMDUtNDJjOC00YjU2LWI3Y2MtNTRhMWY4YzU0YTRlIiwidCI6ImY2MTBjMGI3LWJkMjQtNGIzOS04MTBiLTNkYzI4MGFmYjU5MCIsImMiOjh9
1	Afghanistan	AFG	23-02-2021	NaN	NaN	NaN	NaN	1367.0	NaN	NaN	NaN	34.0	Johnson&Johnson, Oxford/AstraZeneca, Pfizer/BioNTech, Sinopharm/Beijing	World Health Organization	https://app.powerbi.com/view?r=eyJrIjoiYTkyM2VmMDUtNDJjOC00YjU2LWI3Y2MtNTRhMWY4YzU0YTRlIiwidCI6ImY2MTBjMGI3LWJkMjQtNGIzOS04MTBiLTNkYzI4MGFmYjU5MCIsImMiOjh9
2	Afghanistan	AFG	24-02-2021	NaN	NaN	NaN	NaN	1367.0	NaN	NaN	NaN	34.0	Johnson&Johnson, Oxford/AstraZeneca, Pfizer/BioNTech, Sinopharm/Beijing	World Health Organization	https://app.powerbi.com/view?r=eyJrIjoiYTkyM2VmMDUtNDJjOC00YjU2LWI3Y2MtNTRhMWY4YzU0YTRlIiwidCI6ImY2MTBjMGI3LWJkMjQtNGIzOS04MTBiLTNkYzI4MGFmYjU5MCIsImMiOjh9
3	Afghanistan	AFG	25-02-2021	NaN	NaN	NaN	NaN	1367.0	NaN	NaN	NaN	34.0	Johnson&Johnson, Oxford/AstraZeneca, Pfizer/BioNTech, Sinopharm/Beijing	World Health Organization	https://app.powerbi.com/view?r=eyJrIjoiYTkyM2VmMDUtNDJjOC00YjU2LWI3Y2MtNTRhMWY4YzU0YTRlIiwidCI6ImY2MTBjMGI3LWJkMjQtNGIzOS04MTBiLTNkYzI4MGFmYjU5MCIsImMiOjh9
4	Afghanistan	AFG	26-02-2021	NaN	NaN	NaN	NaN	1367.0	NaN	NaN	NaN	34.0	Johnson&Johnson, Oxford/AstraZeneca, Pfizer/BioNTech, Sinopharm/Beijing	World Health Organization	https://app.powerbi.com/view?r=eyJrIjoiYTkyM2VmMDUtNDJjOC00YjU2LWI3Y2MtNTRhMWY4YzU0YTRlIiwidCI6ImY2MTBjMGI3LWJkMjQtNGIzOS04MTBiLTNkYzI4MGFmYjU5MCIsImMiOjh9
5	Afghanistan	AFG	27-02-2021	NaN	NaN	NaN	NaN	1367.0	NaN	NaN	NaN	34.0	Johnson&Johnson, Oxford/AstraZeneca, Pfizer/BioNTech, Sinopharm/Beijing	World Health Organization	https://app.powerbi.com/view?r=eyJrIjoiYTkyM2VmMDUtNDJjOC00YjU2LWI3Y2MtNTRhMWY4YzU0YTRlIiwidCI6ImY2MTBjMGI3LWJkMjQtNGIzOS04MTBiLTNkYzI4MGFmYjU5MCIsImMiOjh9
6	Afghanistan	AFG	28-02-2021	8200.0	8200.0	NaN	NaN	1367.0	0.02	0.02	NaN	34.0	Johnson&Johnson, Oxford/AstraZeneca, Pfizer/BioNTech, Sinopharm/Beijing	World Health Organization	https://app.powerbi.com/view?r=eyJrIjoiYTkyM2VmMDUtNDJjOC00YjU2LWI3Y2MtNTRhMWY4YzU0YTRlIiwidCI6ImY2MTBjMGI3LWJkMjQtNGIzOS04MTBiLTNkYzI4MGFmYjU5MCIsImMiOjh9
7	Afghanistan	AFG	01-03-2021	NaN	NaN	NaN	NaN	1580.0	NaN	NaN	NaN	40.0	Johnson&Johnson, Oxford/AstraZeneca, Pfizer/BioNTech, Sinopharm/Beijing	World Health Organization	https://app.powerbi.com/view?r=eyJrIjoiYTkyM2VmMDUtNDJjOC00YjU2LWI3Y2MtNTRhMWY4YzU0YTRlIiwidCI6ImY2MTBjMGI3LWJkMjQtNGIzOS04MTBiLTNkYzI4MGFmYjU5MCIsImMiOjh9
8	Afghanistan	AFG	02-03-2021	NaN	NaN	NaN	NaN	1794.0	NaN	NaN	NaN	45.0	Johnson&Johnson, Oxford/AstraZeneca, Pfizer/BioNTech, Sinopharm/Beijing	World Health Organization	https://app.powerbi.com/view?r=eyJrIjoiYTkyM2VmMDUtNDJjOC00YjU2LWI3Y2MtNTRhMWY4YzU0YTRlIiwidCI6ImY2MTBjMGI3LWJkMjQtNGIzOS04MTBiLTNkYzI4MGFmYjU5MCIsImMiOjh9
9	Afghanistan	AFG	03-03-2021	NaN	NaN	NaN	NaN	2008.0	NaN	NaN	NaN	50.0	Johnson&Johnson, Oxford/AstraZeneca, Pfizer/BioNTech, Sinopharm/Beijing	World Health Organization	https://app.powerbi.com/view?r=eyJrIjoiYTkyM2VmMDUtNDJjOC00YjU2LWI3Y2MtNTRhMWY4YzU0YTRlIiwidCI6ImY2MTBjMGI3LWJkMjQtNGIzOS04MTBiLTNkYzI4MGFmYjU5MCIsImMiOjh9

Last rows

	country	iso_code	date	total_vaccinations	people_vaccinated	people_fully_vaccinated	daily_vaccinations_raw	daily_vaccinations	total_vaccinations_per_hundred	people_vaccinated_per_hundred	people_fully_vaccinated_per_hundred	daily_vaccinations_per_million	vaccines	source_name	source_website
45974	Zimbabwe	ZWE	11-09-2021	4708905.0	2844848.0	1864057.0	52457.0	44094.0	31.20	18.85	12.35	2922.0	Oxford/AstraZeneca, Sinopharm/Beijing, Sinovac, Sputnik V	Ministry of Health	https://www.arcgis.com/home/webmap/viewer.html?url=https://services9.arcgis.com/DnERH4rcjw7NU6lv/ArcGIS/rest/services/Vaccine_Distribution_Program/FeatureServer&source=sd
45975	Zimbabwe	ZWE	12-09-2021	NaN	NaN	NaN	NaN	42719.0	NaN	NaN	NaN	2831.0	Oxford/AstraZeneca, Sinopharm/Beijing, Sinovac, Sputnik V	Ministry of Health	https://www.arcgis.com/home/webmap/viewer.html?url=https://services9.arcgis.com/DnERH4rcjw7NU6lv/ArcGIS/rest/services/Vaccine_Distribution_Program/FeatureServer&source=sd
45976	Zimbabwe	ZWE	13-09-2021	4752356.0	2856655.0	1895701.0	NaN	41369.0	31.49	18.93	12.56	2741.0	Oxford/AstraZeneca, Sinopharm/Beijing, Sinovac, Sputnik V	Ministry of Health	https://www.arcgis.com/home/webmap/viewer.html?url=https://services9.arcgis.com/DnERH4rcjw7NU6lv/ArcGIS/rest/services/Vaccine_Distribution_Program/FeatureServer&source=sd
45977	Zimbabwe	ZWE	14-09-2021	4800761.0	2873593.0	1927168.0	48405.0	43831.0	31.81	19.04	12.77	2904.0	Oxford/AstraZeneca, Sinopharm/Beijing, Sinovac, Sputnik V	Ministry of Health	https://www.arcgis.com/home/webmap/viewer.html?url=https://services9.arcgis.com/DnERH4rcjw7NU6lv/ArcGIS/rest/services/Vaccine_Distribution_Program/FeatureServer&source=sd
45978	Zimbabwe	ZWE	15-09-2021	4855816.0	2891837.0	1963979.0	55055.0	43249.0	32.17	19.16	13.01	2866.0	Oxford/AstraZeneca, Sinopharm/Beijing, Sinovac, Sputnik V	Ministry of Health	https://www.arcgis.com/home/webmap/viewer.html?url=https://services9.arcgis.com/DnERH4rcjw7NU6lv/ArcGIS/rest/services/Vaccine_Distribution_Program/FeatureServer&source=sd
45979	Zimbabwe	ZWE	16-09-2021	4964302.0	2930550.0	2033752.0	108486.0	51755.0	32.89	19.42	13.48	3429.0	Oxford/AstraZeneca, Sinopharm/Beijing, Sinovac, Sputnik V	Ministry of Health	https://www.arcgis.com/home/webmap/viewer.html?url=https://services9.arcgis.com/DnERH4rcjw7NU6lv/ArcGIS/rest/services/Vaccine_Distribution_Program/FeatureServer&source=sd
45980	Zimbabwe	ZWE	17-09-2021	NaN	NaN	NaN	NaN	45993.0	NaN	NaN	NaN	3047.0	Oxford/AstraZeneca, Sinopharm/Beijing, Sinovac, Sputnik V	Ministry of Health	https://www.arcgis.com/home/webmap/viewer.html?url=https://services9.arcgis.com/DnERH4rcjw7NU6lv/ArcGIS/rest/services/Vaccine_Distribution_Program/FeatureServer&source=sd
45981	Zimbabwe	ZWE	18-09-2021	4992501.0	2940750.0	2051751.0	NaN	40514.0	33.08	19.49	13.59	2684.0	Oxford/AstraZeneca, Sinopharm/Beijing, Sinovac, Sputnik V	Ministry of Health	https://www.arcgis.com/home/webmap/viewer.html?url=https://services9.arcgis.com/DnERH4rcjw7NU6lv/ArcGIS/rest/services/Vaccine_Distribution_Program/FeatureServer&source=sd
45982	Zimbabwe	ZWE	19-09-2021	5015041.0	2948725.0	2066316.0	22540.0	40630.0	33.23	19.54	13.69	2692.0	Oxford/AstraZeneca, Sinopharm/Beijing, Sinovac, Sputnik V	Ministry of Health	https://www.arcgis.com/home/webmap/viewer.html?url=https://services9.arcgis.com/DnERH4rcjw7NU6lv/ArcGIS/rest/services/Vaccine_Distribution_Program/FeatureServer&source=sd
45983	Zimbabwe	ZWE	20-09-2021	5044809.0	2961845.0	2082964.0	29768.0	41779.0	33.43	19.63	13.80	2768.0	Oxford/AstraZeneca, Sinopharm/Beijing, Sinovac, Sputnik V	Ministry of Health	https://www.arcgis.com/home/webmap/viewer.html?url=https://services9.arcgis.com/DnERH4rcjw7NU6lv/ArcGIS/rest/services/Vaccine_Distribution_Program/FeatureServer&source=sd

Overview

Variables

Common Values

Length

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Common Values

Length

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Common Values

Length

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Common Values

Length

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Common Values

Length

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Common Values

Length

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Interactions

Correlations

Spearman's ρ

Pearson's r

Kendall's τ

Cramér's V (φc)

Phik (φk)

Missing values

Sample

First rows

Last rows